ParamHelpers (1.13)

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Helpers for Parameters in Black-Box Optimization, Tuning and Machine Learning.

https://paramhelpers.mlr-org.com
https://github.com/mlr-org/ParamHelpers
http://cran.r-project.org/web/packages/ParamHelpers

Functions for parameter descriptions and operations in black-box optimization, tuning and machine learning. Parameters can be described (type, constraints, defaults, etc.), combined to parameter sets and can in general be programmed on. A useful OptPath object (archive) to log function evaluations is also provided.

Maintainer: Jakob Richter
Author(s): Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Jakob Richter [cre, aut] (<https://orcid.org/0000-0003-4481-5554>), Jakob Bossek [aut], Daniel Horn [aut], Karin Schork [ctb], Pascal Kerschke [aut]

License: BSD_2_clause + file LICENSE

Uses: backports, BBmisc, checkmate, fastmatch, akima, ggplot2, lhs, plyr, testthat, GGally, emoa, gridExtra, reshape2, eaf, irace, covr
Reverse depends: cmaesr, ecr, mlr, mlrCPO, mlrMBO, randomsearch, smoof
Reverse suggests: ChemoSpec2D, dynparam, flacco, llama, OpenML
Reverse enhances: liquidSVM

Released 3 days ago.


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